Automatic detection of multiple oscillations by wavelet analysis

• A wavelet-based method is proposed to detect multiple oscillations.
• The redundant representation precisely indicates the oscillatory behaviors.
• The method is applicable to non-stationary and noisy data due to the multi-resolution wavelet analysis.

This paper proposes an automatic method based on wavelet analysis to detect multiple oscillations in control loops. Continuous wavelet transform provides a way to represent the signal as a superposition of wavelets. The redundancy of the representation can be exploited to precisely indicate the location of oscillatory behaviors in the time-frequency plane. Oscillatory components are separated by the adaptive design of filter bank. It uncovers all the zero-crossings in the frequency bands which possibly include oscillations to be confirmed by Auto-covariance Function (ACF). The method is applicable to non-stationary and noisy data due to the multi-resolution analysis of orthonormal wavelet bases. This paper ends with demonstrating the effectiveness of the proposed method with benchmark industrial data.

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